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Why is it that highly trained and seasoned executives fail? On the surface, this doesn’t make sense because they are very successful; yet research in the organization sciences provides no shortage of evidence to prove just that. From the classic Mann Gulch fire disaster of Weick’s famous collapse of sensemaking study, to studies of myopia of learning, escalation of commitment, threat-rigidity, dominant logic, the architecture of simplicity, the Icarus Paradox, to core competencies turning into core rigidities, and navigating new competitive markets using “old” cognitive maps, and many more such examples point to a ubiquitous phenomenon where highly trained and experienced professionals find themselves “stuck” in the heat of battle, unable to move and progress. On the one hand, for some, there is a desperate need for change, but are unable to do so, due to their trained incapacities. On the other hand, some simply cannot see the need for change, and continue with their “business as usual” mentality. For both, their visions of the world shrink, they have a tendency to cling onto their past habitual practices and oversimplify the complexity of the situation. In moments like these: DROP YOUR TOOLS and UNLEARN! This book chapter introduces a framework (grounded in clinical psychology) that has had consistent success in helping seasoned executives and key decision-makers open up the alternatives whenever they find themselves stuck with complexity.

Despite the increasing use of home delivery (HD) in e-commerce, no studies have explicitly examined consumer perceptions of the convenience of the last-mile delivery of goods by cargo bike (CB). Therefore, this study aims to identify the dimensions of HD convenience and to develop a reliable and valid measurement tool, namely the Home-Delivery Convenience via Cargo Bike (HDCCB) scale.

The methodology of this scale development study is premised on a review of the existing literature, which identifies differences in consumer perceptions of the convenience of services. The authors conducted semi-structured interviews with 10 online consumers and validated the content with 3 experts on marketing in the retail and services sectors in order to develop the items for the scale. Thereafter, the authors identified the main dimensions through an exploratory factor analysis that the authors applied to an online survey with 116 respondents. Finally, the scale was validated through a confirmatory factor analysis of an online survey with 300 respondents.

Following the original work of Brown (1990), the authors define consumer perceptions of HD convenience as a multidimensional construct and measure each facet of its four dimensions, which are time, use, execution and acquisition. E-retailers and last-mile logistics providers could use the authors' proposed measurement tool to assess consumer perceptions of the convenience of HD. That assessment could generate a competitive advantage.

This study is original as the study deepens the existing understanding of consumer perceptions of the convenience of HD by CB in last-mile logistics. This study also develops a multidimensional measure that is based on an empirical study.

This study aims to examine the factors influencing trust toward mobile health applications (mhealth apps) among young consumers. By building on the socio-technical systems framework and self-congruence theory, the authors develop and examine a conceptual model of the trusting intentions of young consumers toward mhealth apps.

The data for the study was collected from a sample of 285 young consumers via an online survey by using a purposive sampling method. All the respondents were existing users of health apps and resided in the urban areas of the country. The sample comprised 53% male respondents and 47% female respondents. Subsequently, the data was analyzed using the structural equation modeling technique.

The findings revealed that psychological factors like self-congruence and technical factors such as flow experience and perceived playfulness aid in building trust among young mhealth app users, which in turn influences the purchase intention and user loyalty toward the application. Social factors like perceived critical mass and social influence did not significantly impact trust.

The data was collected from Generation Z, recognized as the most influential consumer demographic worldwide, primarily involved in mhealth app usage. Nonetheless, it is essential to understand that these findings might only partially apply to a specific user group. In addition, the study did not focus on any specific mhealth applications. Hence, it is prudent to exercise caution when generalizing these results to the broader population.

This study advances the comprehension of socio-technical elements in establishing trust, subsequently impacting purchase intentions and loyalty among young users in the context of mhealth apps. In addition, it expands the socio-technical framework by incorporating a psychological factor that could influence trust and purchase intentions toward mhealth apps. Furthermore, the post hoc findings reinforce this comprehension by identifying the moderating effects of operating system type and gender. These insights could provide valuable guidance for developing tailored marketing strategies targeting the young consumer base.

This study aims to investigate the role of interpersonal influence on consumer purchase decisions regarding foreign products, specifically by exploring consumers’ social reaction styles (acquisitive and protective) when confronted with normative pressures and their subsequent impact on consumers’ purchase behavior in the context of situational animosity.

Three studies were conducted in China to empirically examine the proposed research model. The US–China Chip War of 2022 was used as the research context for situational animosity, while the Japan–China relationship representing a stable animosity condition was used for contrast.

This study establishes the mediating role of perceived normative pressure in linking animosity attitudes to purchase avoidance in situational animosity. It also validates that consumers’ social reaction styles (acquisitive and protective) help predict distinct behavioral outcomes, holding significant implications for advancing research in the field of product and brand consumption.

This research provides a novel perspective by exploring consumers’ social reaction styles when dealing with normative pressure in situational animosity. The distinction between acquisitive and protective reaction styles adds depth and originality to the study. Moreover, this study examines consumer behavior in two distinct consumption contexts: switching intentions to local products and purchase intentions for products from offending countries in hidden consumption situations. This dual perspective offers a comprehensive exploration of consumers’ purchase behavior under normative pressure, contributing to the novelty of this research.

The growth of the global labor force and business analytics has significantly impacted human resource management (HRM). Human resource (HR) analytics is an emerging field that creates value for employees and organizations. By examining the existing studies on HR analytics, the paper systematically reviews the literature to identify active research areas and establish a roadmap for future studies in HR analytics.

A portfolio of 503 articles collected from the Scopus database was reviewed. The study has adopted a Latent Dirichlet allocation (LDA) topic modeling approach to identify significant themes in the literature.

The HR analytics research domain is classified into four categories: HR functions, statistical techniques, organizational outcomes and employee characteristics. The study has also developed a framework for organizations adopting HR analytics. Linking HR with blockchain technology, explainable artificial intelligence and Metaverse are the areas identified for future researchers.

The framework will assist practitioners in identifying statistical techniques for optimizing various HR functions. The paper discovers that by implementing HR analytics, HR managers and business partners can run reports, make dashboards and visualizations and make evidence-based decision-making.

The previous studies have not applied any machine learning techniques to identify the topics in the extant literature. The paper has applied machine learning tools, making the review more robust and providing an exhaustive understanding of the domain.

Stereolithography (SLA) additive manufacturing (AM) technique has enabled the production of inconspicuous and aesthetically pleasing orthodontics that are also hygienic. However, the staircase effect poses a challenge to the application of invisible orthodontics in the dental industry. The purpose of this study is to implement chemical postprocessing technique by using isopropyl alcohol as a solvent to overcome this challenge.

Fifteen experiments were conducted using a D-optimal design to investigate the effect of different concentrations and postprocessing times on the surface roughness, material removal rate (MRR), hardness and cost of SLA dental parts required for creating a clear customized aligner, and a container was constructed for chemical treatment of these parts made from photocurable resin.

The study revealed that the chemical postprocessing technique can significantly improve the surface roughness of dental SLA parts, but improper selection of concentration and time can lead to poor surface roughness. The optimal surface roughness was achieved with a concentration of 90 and a time of 37.5. Moreover, the dental part with the lowest concentration and time (60% and 15 min, respectively) had the lowest MRR and the highest hardness. The part with the highest concentration and time required the greatest budget allocation. Finally, the results of the multiobjective optimization analysis aligned with the experimental data.

This paper sheds light on a previously underestimated aspect, which is the pivotal role of chemical postprocessing in mitigating the adverse impact of stair case effect. This nuanced perspective contributes to the broader discourse on AM methodologies, establishing a novel pathway for advancing the capabilities of SLA in dental application.

Prior research has highlighted the pervasive importance of digital technologies in business and societal settings, but their enabling role in digital transformation, and effective forms of organization to address tensions that arise during attempts to promote it, have been insufficiently explored. Therefore, the purpose of this paper is to investigate how and why tensions affect clusters established to foster digital transformation.

Empirical data were acquired through a qualitative exploratory holistic single case study, focused on the Swedish Cluster of Forest Technology. This included interviews with informants, selected by homogeneous purposive sampling, and event observation to investigate the personal perspectives of representatives of every company engaged in the cluster, followed by a thematic analysis of their comments.

The case study revealed three major tensions, between knowledge flow, collaboration and competition, but also others that were interrelated with those major tensions, related to matters such as trust and protection of intellectual property, power equality and hierarchy, and networks that must be managed in digital transformation efforts.

The paper extends understanding of the tensions that arise, and their management, in digital transformation processes.